Financial Algorithms And What it Means For Your Business November 19, 2018November 28, 2018 Rob LaPointefinancial algorithmsLeave a Comment on Financial Algorithms And What it Means For Your Business What Is An Algorithm Most of us have become familiar with the word algorithm and that it has to do with technology, making things work and providing information. That is true, but let’s break it down. 1 single algorithm provides the same info that it is given, so as you combine algorithms they can then perform more complex tasks that provide more useful information. Computers help us by providing programs which allow us to complete tasks. In order for us to do that the program has to create and be given instructions on how to do something for each scenario. An algorithm is what tells the computer exactly what it needs to do in order for you to get the desired task completed. For example, an algorithm will ask for a piece of information from you and then it takes that information and dictates what needs to be done with it. Algorithms are different than codes so don’t get them confused. For one thing, algorithms are much easier to understand than codes are. They are pretty much like a flow chart which shows all the steps from start to finish and all the different paths that can be taken. Financial Algorithms for Business As a business owner, you can use financial algorithms to perform many different tasks to help improve your top line and bottom line. Imagine being able to pinpoint the creditworthiness of future customers. It can even go as far as making predictions of whether or not something could go wrong in the future. Technology has made it possible to do a lot more than ever before, creating a better, more accurate decision-making process. Although there are many different ways you can use algorithms, using it for finance is one of the best ways. There are definitely some ways your business could be implementing them to help with your business goals. The Digital Footprint Most businesses have a system in place which helps give them an idea of which amount of credit to extend to customers who fall within a certain category. Everything a person does in the digital world can be taken into account. We are so used to gathering a certain list of basic information to determine this but you will be surprised with the right financial algorithms how much more information can be used to provide you with more accurate answers. Traditional methods can’t quite measure up to big data anymore. Consumers must understand that everything they do digitally is recorded and used for data purposes. You may notice those cookie pop-ups when you go to a website. The data that these algorithms use isn’t going to give perfect results of course which is why more information is key. Whether you are on the consumer side or business side these are the items being tracked to determine financial stats: 1. The brand of phone you buy 2. The type of car you own 3. The type of device you use to make your purchases 4. Your internet path to get to a particular website 5. The time you make your purchases 6. Your email address All of this information which is very common whenever anyone makes a purchase can be tracked and used to help businesses makes decisions about their potential customers. It’s easy to find this information because all of these websites ask for basic information to register when you make a purchase. They can track how you ended up on their website, if you came onto the site using a desktop computer, if you made the purchase in the middle of the day, what your email is and more. All of this data gives us insight into who that person is. There are specific statistics to determine the likelihood that potentials customers could default and that all has to do with that information. If you combine the data you find here with their credit score you will get much more accurate results. The Downside There are many arguments that this is unreliable data and can be used the wrong way. For example, maybe you are great with money and don’t have any credit issues but your online footprint tells a different story. This is likely to happen because people don’t always follow the typical pattern. Variables have to be taken into account because if they are not your data will end up being inaccurate. Our activity online isn’t usually given much thought so the statistics gathered can be somewhat misleading. As a business, this has to be taken into account. The other downside is this type of data gathering can end up basing things on age, race, and gender which can cause serious problems. This needs to be taken seriously because letting these financial algorithms determine someone’s creditworthiness based on those details means not only discrimination but also accuracy problems. The Upside There are some serious downsides businesses need to understand before implementing these financial algorithms. However, if done correctly it can provide amazing results. With that in mind, it doesn’t just help business with results but also helps your customers too. Those who may not have gotten approved could actually have a better chance of getting approved. The Realization It’s not just about creditworthiness but so much more. This kind of data if gathered correctly can make it easier to determine loan amounts, credit approval and the interest rate amounts, who to hire, insurance approvals and amounts, and much more. These algorithms are far from perfect. There are still many problems that need to be fixed. The accuracy of the data can easily be called into question. People don’t necessarily know why they get denied for something and the creators of these financial algorithms can’t always figure it out either or why the data may not be accurate. Now is the time to create useful financial algorithms that can do things correctly. This is the future and we are just at the beginning of what this technology can do for not only you personally but your business as well. If you have more questions about building algorithms into your business contact Rob LaPointe at 408.802.2885 or email him email@example.com.